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With the recent proliferation of AI, organisations are transforming not only their organisational design but also the input and output operational processes of the hiring process. The purpose of this paper is to explore the organisational and operational dimensions resulting from the deployment of AI during talent acquisition process.

The authors conducted semi-structured interviews and meetings with human resources (HRs) professionals, recruiters and AI hiring platform providers in Sweden. Using an inductive data analysis rooted in the principles of grounded theory, the study uncovered four aggregate dimensions critical to understanding the role of AI in talent acquisition.

With insights from algorithmic management and ambidexterity theory, the study presents a comprehensive theoretical framework that highlights four aggregate dimensions describing AI’s transformative role in talent recruitment. The results provide a cautionary perspective, advising against an excessive emphasis on operational performance driven solely by algorithmic management.

The study is limited in scope and subject to several constraints. Firstly, the sample size and diversity are restricted, as the findings are based on a limited number of semi-structured interviews and meetings with HRs professionals, recruiters, and AI hiring platform providers. Secondly, the rapid evolution of AI technologies means that the study’s findings may quickly become outdated as new advancements and applications emerge.

The results provide managers with actionable information that can lead to more precise and strategic management practices, ultimately contributing to improved organizational performance and outcomes. Plus, enhancing their ability to make informed decisions, optimize processes and address challenges effectively.

The results signal both positive and negative impacts on employment opportunities. On the positive side, AI can streamline recruitment processes, making it easier for qualified candidates to be identified and hired quickly. However, AI systems can also perpetuate existing biases present in the data they are trained on, leading to unfair hiring practices where certain groups are systematically disadvantaged.

By examining the balance between transactional efficiency and relational engagement, the research addresses a crucial trade-off that organizations face when implementing AI in recruitment. The originality lies in its critique of the prevailing emphasis on e-recruiting.

The role of construction industry in harnessing human and material resources of a nation cannot be overemphasised; hence, the emergence of the requirement of leadership. This study aims to assess the usage of factors of transactional leadership style (TSLS) by the project managers (PMs) in the Nigeria construction industry.

A survey research design approach with questionnaire as an instrument of gathering data was adopted. Out of 1,233 questionnaires distributed, data from 975 received with acceptable feedback were analysed using both descriptive and inferential statistics.

This study revealed the following factors under active management by exception as the TSLS factors often employed by PMs in Nigeria. These factors are the three frequently used factors: they are: “always give clear and final instructions to be implemented in the project”; “always observed the progress of the project, assessed risk and took precaution to avoid mistakes in the project”; and “always closely monitor performance for errors needing correction”. This study concludes that it is imperative for PMs in the study area to adopt and incorporate these factors to ensure continuous successful delivery of construction projects.

Therefore, it is hoped that the findings of this research will help the construction industry managers to address the age-long but unrecognised leadership problem confronting the sector, thereby boosting project delivery.

The findings establish the appropriateness or otherwise of adoption of factors of transactional leadership, either in part or a whole.

This study aims to explore the impact of athlete brand image on fans’ social media engagement, purchase intentions, and also examines the mediating role of emotional attachment on these relationships, as well as the moderating role of perceived price value between emotional attachment and purchase intentions.

The data are based on an online survey conducted in China (N = 572). The PLS-SEM (partial least squares structural equation model) and regression-based estimation method (PROCESS) are employed to test the hypotheses.

The results indicate a positive relationship between athletes’ athletic performance and fans’ social media engagement as well as purchase intentions. The impact of athletes’ attractive appearance and marketable lifestyle on fans’ purchase intentions is sequentially mediated by emotional attachment and social media engagement. Moreover, the mediation effect of athletes’ off-field image and purchase intentions is contingent upon fans’ perceived price value.

Athletes and marketers could integrate and leverage both the on-field and off-field attributes to cultivate emotional connections with fans. Sports organizations and managers need to pay attention to fans’ social media engagement and provide content that increases engagement and converts into transactional behavioural intentions.

The study provides empirical evidence of the mediating role of emotional attachment between athlete brand image and fans’ purchase intentions. The explanatory mechanisms involving emotional attachment and social media engagement (non-transactional behavioural intentions) are anticipated to be a noteworthy addition to the traditional fan transactional behavioural intentions framework. Moreover, the research introduces and confirms perceived price value as a crucial moderating factor influencing the relationship between emotional attachment and purchase intentions.

Despite the growing interest in blockchain technology (BCT) applications in the agri-food industry, evidence of their economic and strategic implications remains scarce. This study aims to contribute to filling this gap by jointly investigating how BCT adoption affects transactional relationships, and how it contributes to the firm’s strategic resources.

An explanatory case study is conducted based on a theoretical framework grounded on transaction cost economics and the resource-based-dynamic capabilities view. Six BCT implementations by agri-food firms are studied. Data were collected through semi-structured interviews and analysed using thematic analysis.

Findings reveal that BCT benefits depend on how companies integrate technology across their supply chains. In fact, the results suggest that overall transaction efficiency within the supply chain is enhanced only for those firms prioritising stakeholder engagement during technology implementation and leveraging existing trust relationships with economic agents. Moreover, the results suggest that BCT is not yet perceived as a strategic resource, but rather that it has the potential to enhance firms’ operational-adaptive, absorptive and innovative capabilities. When all supply chain actors clearly understand blockchain’s functionality and value, the development of these capabilities becomes more pronounced.

The study identifies two BCT adoption configurations. One primarily focuses on enhancing supply chain efficiency and transparency (dynamic BCT), while the other uses BCT mainly for marketing purposes (static BCT). These configurations lead to varied possibilities for leveraging BCT’s potential advantages. Furthermore, they show how a mismatch between a strategic approach and its chosen configuration could work against any positive impact and lead to disillusionment with the BCT. Thus, managers should assess carefully the impact of such different configuration choices on performance.

To the best of the authors’ knowledge, this is the first study to attempt to analyse the economic implications of adopting BCT in the food sector from both a firm and supply chain perspective. Additionally, it shows how interpreting these impacts is contingent on the diverse modalities for embedding BCT into existing supply chains.

This study investigates the sustainability models of non-profit and hybrid organizations, which aim to balance economic, social and environmental objectives. The research introduces the Sustainability Model Canvas to analyze these organizations and identify common patterns, unique characteristics and managerial insights to balance the triple bottom line.

The research utilizes the Sustainability Model Canvas to examine the sustainability models of 200 non-profit and hybrid organizations. Data were collected from secondary sources, including articles, reports and websites. The analysis was conducted using the activity system theoretical framework, which helped to identify design elements and themes within the business models of the studied organizations.

The study reveals four primary sustainability model patterns: donated income, earned income, public income and auto-generated income. An additional mixed approach pattern is identified, combining elements from the four primary patterns. The research highlights the parallels between these sustainability models and multi-sided platform business models, offering managerial suggestions for leveraging these patterns to achieve sustainability.

The study is based on secondary data, which may limit the depth of insights compared to primary data collection. At the same time, the chance to consider hybrid organization through multi-sided platform lenses provides relevant contributions to both the literature streams.

The identified sustainability model patterns and managerial suggestions can serve as blueprints for non-profit and hybrid organizations aiming to design or innovate their sustainability models. The Sustainability Model Canvas offers a practical tool for organizations to visualize and balance their triple bottom line objectives.

The research underscores the importance of integrating social and environmental considerations into business models, promoting a holistic approach to sustainability that can lead to broader social and environmental benefits.

This research contributes to the business model literature by extending the focus beyond traditional profit-oriented organizations to include non-profit and hybrid organizations. The introduction of the Sustainability Model Canvas provides a new tool for designing and analyzing sustainability-oriented business models. The study also suggests considering sustainability models as multi-sided platforms, offering new insights for both academic and practical applications.

The purpose of this paper is to explore networked business models on a nascent market for a sustainable innovation.

The study takes a qualitative approach through a comparative case study of three solar photovoltaic (PV) parks in Sweden. Data was collected from 14 interviews with multiple supply chain and network actors as well as secondary data. Industrial marketing and purchasing is applied for theoretical framing.

The study demonstrates transactional, relational, environmental and social drivers for participating in the network. The study reveals the duplicity of the nascent market, which encourages supply chain actors to develop their individual business models to take a larger market share or become future competitors to current collaborators. On the nascent market with few developed regulations, the network enables actors to influence regulations on local and regional levels.

The study is limited to the nascent solar PV industry in Sweden, which is characterized by institutional turbulence, market uncertainties and few established supply networks.

Practitioners need to consider multifarious drivers for participating in networked business models, where the economic driver may be the least motivating.

This study provides several multiactor business models and classifies them into specific applications and general applications. The study provides unique insight into the complexity of interactions among supply chain actors in networked business models on a nascent market for sustainable innovation. Due to the scarcity of available partners on the nascent market, actors need to look beyond their on-going relationships and their network horizon, or actors’ roles evolve to include activities that was not part of their individual business models.

The aim of this study is to explore employees’ perceptions of the role of human resources (HR) departments in Jordanian organisations and the reasons behind these perceptions.

Semi-structured interviews were conducted with 23 employees who work at different organisations in various industrial sectors in Jordan.

Employees perceive HR roles as: providing transactional services (traditional); working as business partners to facilitate other departments’ roles (limited). Perceptions of HR professionals and the role of HR departments were generally negative, due to: societal-cultural norms and stereotypes of HR departments and HR professionals; the role of Wasta (a localised form of favouritism) in affecting HR practices; employees’ personal experiences with HR departments and HR professionals at their workplace; and the non-availability of human resources management (HRM) degrees in Jordan.

Limited research has explored varying perceptions about HR departments and their impacts on business contexts in emerging markets, including Jordan. This research is unique as it identifies the reasons behind common misconceptions of HR roles in Jordanian organisations. It extends beyond existing literature by integrating employees’ perceptions of the role of the HR departments to understand the consequences for HR practices’ operational effectiveness. It also pioneers consideration of societal culture in shaping these perceptions, which helps us build theories for future testing and generalisation purposes in other contexts with cultural commonalities. This study also highlights the current state of HRM development in Jordan, which helps in setting the agenda for future research in the country and the Middle East and North Africa region.

This paper is a response to the failure of construction firms to use sufficient attention to their working capital management (WCM) practices, resulting in operational challenges, and leading to the collapse of firms in most developing countries. Hence, this study aims to explore the empirical perspective of WCM practices among large building construction firms (LBCFs) in Ghana, to help achieve the Sustainable Development Goal 9.

The study collected primary data through structured survey questionnaires from LBCFs in Ghana. The CEOs/Directors, General Managers and Accountant/Finance of LBCFs in Ghana formed the unit of analysis based on a simple random sampling technique. Mean score, standard deviation and one-sample t-test were used to perform the empirical analysis of the study.

According to this study's empirical results, LBCFs appear to have effective WCM practices in place. This was evidenced in the surveyed responses which indicate that the sector’s WCM practices sound good based on the mean scores and statistically significant as the t-values > 1.664. Notably, LBCFs in Ghana pay their suppliers early to reduce the fear of adverse effect of late payments on their credit history, making them conservative in their approach toward financial management.

This is a pioneering paper in a developing country like Ghana, highlighting the significance of gaining an in-depth understanding of WCM practices among LBCFs. The findings of this study are expected to provide valuable information to industry players toward ensuring WCM efficiencies and can serve as a solid foundation for further empirical studies.

Increased competition and the constant need for companies to differentiate make markets more competitive and consumers more demanding when making purchasing decisions. Consequently, companies recognized the importance of marketing and economics, which has gradually replaced its transactional practices, focused essentially on a single transaction, with relational practices, in which the customer is considered an integral part of the process. Creating long and profitable relationships has become a business priority and the use of tools such as customer relationship marketing (CRM) has become crucial. With the increasing importance of health and wellness tourism, thermalism has become a very competitive product wanted by tourists who need treatments that are not available in their country due to lack of availability or because they are quite expensive. Since tourism is integrated in the services sector, a set of relational marketing strategies can be applied to establish and maintain relationships with tourists. Therefore, it is important to understand how relational marketing can improve health and wellness tourism. Based on a combination of theoretical and practical research, this chapter explores the dynamic system and mechanism of innovation and development of relational marketing strategies in specific contexts of tourism (i.e. health and wellness tourism) considering cross-border (i.e. Northern Euroregion of Portugal and Galicia). From an interdisciplinary perspective, the chapter presents insights for marketing and tourism (health and well-being) and for the economic development of territories (i.e. cross-border regions).

The complexity of citizenship behavior in organizations has long been a focus of research. Traditional methodologies have been predominantly used to address this complexity. This paper aims to tackle the problem using a cutting-edge technological tool: business process mining. The objective is to enhance citizenship behaviors by leveraging primary data collected from 326 white-collar employees in the Indian service industry.

The study focuses on two main processes: training and creativity, with the ultimate goal of fostering organizational citizenship behavior (OCB), both in its overall manifestation (OCB-O) and its individual components (OCB-I). Seven different machine learning algorithms were used: artificial neural, behavior, prediction network, linear discriminant classifier, K-nearest neighbor, support vector machine, extreme gradient boosting (XGBoost), random forest and naive Bayes. The approach involved mining the most effective path for predicting the outcome and automating the entire process to enhance efficiency and sustainability.

The study successfully predicted the OCB-O construct, demonstrating the effectiveness of the approach. An optimized path for prediction was identified, highlighting the potential for automation to streamline the process and improve accuracy. These findings suggest that leveraging automation can facilitate the prediction of behavioral constructs, enabling the customization of policies for future employees.

The findings have significant implications for organizations aiming to enhance citizenship behaviors among their employees. By leveraging advanced technological tools such as business process mining and machine learning algorithms, companies can develop more effective strategies for fostering desirable behaviors. Furthermore, the automation of these processes offers the potential to streamline operations, reduce manual effort and improve predictive accuracy.

This study contributes to the existing literature by offering a novel approach to addressing the complexity of citizenship behavior in organizations. By combining business process mining with machine learning techniques, a unique perspective is provided on how technological advancements can be leveraged to enhance organizational outcomes. Moreover, the findings underscore the value of automation in refining existing processes and developing models applicable to future employees, thus improving overall organizational efficiency and effectiveness.